A Hybrid Data-driven Deep Learning Technique for Fluid-Structure Interaction
A Hybrid Data-driven Deep Learning Technique for Fluid-Structure Interaction
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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This paper is concerned with the development of a hybrid data-driven technique for unsteady fluid-structure interaction systems. The proposed data-driven technique combines the deep learning framework with a projection-based low-order modeling. While the deep learning provides low-dimensional approximations from datasets arising from black-box solv...
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A Hybrid Data-driven Deep Learning Technique for Fluid-Structure Interaction
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TN_cdi_proquest_journals_2092809719
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2092809719
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2331-8422